Monkey
think, cursor do

By
Eric Smalley,
Technology Research NewsComputers fall far short of being able
to read our minds. This could change. Brown University researchers have
shown that, with the right filters, computers can interpret the electrical
signals brain cells send to move limbs.

The researchers implanted electrodes in the brains of three rhesus monkeys
and recorded neural activity as each monkey used a hand control to move
the cursor on a computer screen. The implant, a centimeter-wide silicon
chip covered with tiny spikes, recorded the signals from a small number
of motor neurons in the monkeys' brains.

The researchers then built a mathematical algorithm that converted these
neural signals into a control signal that moved the cursor. The algorithm
translated the brain signals into computer signals in real-time, which
allowed the monkeys to pursue a moving spot on the computer screen with
the cursor just by moving their arms.

The algorithm averages the signals from 7 to 30 motor neurons to estimate
where each monkey intends to move its hand. "It's as if each neuron
gets a series of votes on where it thinks the hand is," said Mijail
Serruya, a graduate student at Brown University. "Some of the votes
relate to how the neuron feels right now, some relate to how it felt up
to one second ago. The model... uses this to guess new hand positions
from the neural activity alone," he said.

The researchers' system was able to produce a control signal after recording
only a few minutes of the monkeys' manual control of the cursor, according
to Mijail Serruya, a graduate student at Brown University.

"The scientific principle of decoding [motor neuron] activity rapidly,
online, in a useful manner is now proven," said Serruya. the method could
eventually help people who are paralyzed control electronic devices, he
said. "This paves the way for possible development of a medical device
that could help paralyzed patients."

One monkey eventually learned to control the cursor without visibly moving
its arm. The researchers could not determine whether the monkey was using
subtle muscle movements to produce the neural signals, however, and so
do not yet know whether thought alone can be used to produce the control
signal.

The neural control was as efficient as hand control at the task of pursuing
the spot on the screen, said Serruya.

Paralyzed humans have already used brain implants to control computer
screen cursors. But in those experiments, the subjects took months to
learn how to use the system, said Serruya. "Any neuroprosthetic system
requires both the machine and the person to learn," he said. "We believe
that by having our machine -- the mathematical algorithm -- do a lot of
learning, it makes it much easier and faster for the subject to learn
their part."

In a similar experiment last year, researchers at Duke University, the
Massachusetts Institute of Technology and the State University of New
York Health Science Center used a monkey's motor neuron signals to control
a robotic arm. In that case, the robot arm simply mimicked the actions
of the monkey's arm, and the monkey did not consciously control the robot
arm.

The Brown University monkeys controlled the cursors consciously in order
to win rewards.

The researchers are considering applying their technique to other output
devices, said Serruya. It's too soon to estimate when or if the technique
could be applied to humans, he said.

Serruya's research colleagues were Matthew R. Fellows and John P. Donoghue
of Brown University, and Nicholas G. Hatsopoulos and Liam Paninski who
are now at the University of Chicago. They published the research in the
March 14, 2002 issue of the journal Nature. The research was funded by
the National Institute of Neurological Diseases and Stroke, the Defense
Advanced Research Projects Agency (DARPA) and the Burroughs Welcome Foundation.